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      Population bottlenecks constrain host microbiome diversity and genetic variation impeding fitness

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          Abstract

          It is becoming increasingly clear that microbial symbionts influence key aspects of their host’s fitness, and vice versa. This may fundamentally change our thinking about how microbes and hosts interact in influencing fitness and adaptation to changing environments. Here we explore how reductions in population size commonly experienced by threatened species influence microbiome diversity. Consequences of such reductions are normally interpreted in terms of a loss of genetic variation, increased inbreeding and associated inbreeding depression. However, fitness effects of population bottlenecks might also be mediated through microbiome diversity, such as through loss of functionally important microbes. Here we utilise 50 Drosophila melanogaster lines with different histories of population bottlenecks to explore these questions. The lines were phenotyped for egg-to-adult viability and their genomes sequenced to estimate genetic variation. The bacterial 16S rRNA gene was amplified in these lines to investigate microbial diversity. We found that 1) host population bottlenecks constrained microbiome richness and diversity, 2) core microbiomes of hosts with low genetic variation were constituted from subsets of microbiomes found in flies with higher genetic variation, 3) both microbiome diversity and host genetic variation contributed to host population fitness, 4) connectivity and robustness of bacterial networks was low in the inbred lines regardless of host genetic variation, 5) reduced microbial diversity was associated with weaker evolutionary responses of hosts in stressful environments, and 6) these effects were unrelated to Wolbachia density. These findings suggest that population bottlenecks reduce hologenomic variation (combined host and microbial genetic variation). Thus, while the current biodiversity crisis focuses on population sizes and genetic variation of eukaryotes, an additional focal point should be the microbial diversity carried by the eukaryotes, which in turn may influence host fitness and adaptability with consequences for the persistence of populations.

          Author summary

          It is becoming increasingly clear that organisms and the microbes that live on or in them–their microbiome–affect each other in profound ways that we are just beginning to understand. For instance, a diverse microbiome can help maintain metabolic functions or fight pathogens causing diseases. A disrupted microbiome may be especially critical for animals and plants that occur in low numbers because of threats from e.g. human exploitation or climate change, as they may already suffer from genetic challenges such as inbreeding and reduced evolutionary potential. The importance of such a reduction in population size, called a bottleneck, on the microbial diversity and the potential interactive effects on host health remains unexplored. Here we experimentally test these associations by investigating the microbiomes of 50 inbred or non-inbred populations of vinegar flies. We found that restricting the population size constrain the host’s genetic variation and simultaneously decreases the diversity of the microbiome that they harbor, and that both effects were detrimental to host fitness. The microbial communities in inbred host populations were less robust than in their non-inbred counterparts, suggesting that we should increasingly consider the microbiome diversity, which may ultimately influence the health and persistence of threatened species.

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          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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            Fitting Linear Mixed-Effects Models Usinglme4

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              QIIME allows analysis of high-throughput community sequencing data.

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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: SoftwareRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: SoftwareRole: VisualizationRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: InvestigationRole: ResourcesRole: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: ResourcesRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS Genet
                PLoS Genet
                plos
                PLoS Genetics
                Public Library of Science (San Francisco, CA USA )
                1553-7390
                1553-7404
                23 May 2022
                May 2022
                : 18
                : 5
                : e1010206
                Affiliations
                [1 ] Section for Zoophysiology, Department of Biology, Aarhus University, Aarhus, Denmark
                [2 ] Section for Bioscience and Engineering, Department of Chemistry and Bioscience, Aalborg University, Aalborg, Denmark
                [3 ] Institute for Plant Sciences, Department of Biology, University of Cologne, Cologne, Germany
                [4 ] School of Biosciences, Bio21 Molecular Science and Biotechnology Institute, University of Melbourne, Melbourne, Australia
                University of Georgia, UNITED STATES
                Author notes

                The authors have declared that no competing interests exist

                Author information
                https://orcid.org/0000-0001-8222-8399
                Article
                PGENETICS-D-21-01334
                10.1371/journal.pgen.1010206
                9166449
                35604942
                4a03a8b6-c437-42f1-80cf-fa18148720c3
                © 2022 Ørsted et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 18 November 2021
                : 18 April 2022
                Page count
                Figures: 6, Tables: 2, Pages: 23
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/100008393, teknologi og produktion, det frie forskningsråd;
                Award ID: DFF-0170-00006B
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100008394, natur og univers, det frie forskningsråd;
                Award ID: DFF-0136-00171B
                Award Recipient :
                Funded by: australien research council
                Award ID: DP120100916
                Award Recipient :
                This study was funded by the Independent Research Fund Denmark (grants DFF-0170-00006B to MØ and DFF-0136-00171B to TNK), and partly by the Australian Research Council (DP120100916 to AAH). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Evolutionary Biology
                Population Genetics
                Genetic Polymorphism
                Biology and Life Sciences
                Genetics
                Population Genetics
                Genetic Polymorphism
                Biology and Life Sciences
                Population Biology
                Population Genetics
                Genetic Polymorphism
                Biology and Life Sciences
                Microbiology
                Medical Microbiology
                Microbiome
                Biology and Life Sciences
                Genetics
                Genomics
                Microbial Genomics
                Microbiome
                Biology and Life Sciences
                Microbiology
                Microbial Genomics
                Microbiome
                Biology and Life Sciences
                Genetics
                Microbial Genetics
                Biology and Life Sciences
                Evolutionary Biology
                Population Genetics
                Biology and Life Sciences
                Genetics
                Population Genetics
                Biology and Life Sciences
                Population Biology
                Population Genetics
                Biology and Life Sciences
                Ecology
                Ecological Metrics
                Species Diversity
                Ecology and Environmental Sciences
                Ecology
                Ecological Metrics
                Species Diversity
                Biology and Life Sciences
                Biochemistry
                Nucleotides
                Biology and Life Sciences
                Genetics
                Heredity
                Inbreeding
                Biology and Life Sciences
                Evolutionary Biology
                Evolutionary Genetics
                Custom metadata
                vor-update-to-uncorrected-proof
                2022-06-03
                Additional data can be found in the Supporting Information files. 16S RNA data have been deposited under the SRA Bioproject (accession number PRJNA813140) at NCBI.

                Genetics
                Genetics

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